class TUnfold: public TObject

TUnfold provides functionality to correct data
for migration effects.

Citation: S.Schmitt, JINST 7 (2012) T10003 [arXiv:1205.6201]


TUnfold solves the inverse problem

T   -1            2          T
chi**2 = (y-Ax) Vyy  (y-Ax) + tau  (L(x-x0)) L(x-x0)

Monte Carlo input
y: vector of measured quantities  (dimension ny)
Vyy: covariance matrix for y (dimension ny x ny)
A: migration matrix               (dimension ny x nx)
x: unknown underlying distribution (dimension nx)
Regularisation
tau: parameter, defining the regularisation strength
L: matrix of regularisation conditions (dimension nl x nx)
x0: underlying distribution bias

where chi**2 is minimized as a function of x

The algorithm is based on "standard" matrix inversion, with the
known limitations in numerical accuracy and computing cost for
matrices with large dimensions.

Thus the algorithm should not used for large dimensions of x and y
dim(x) should not exceed O(100)
dim(y) should not exceed O(500)